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Pathway Solver

Pathway Solver sizes the plus-internal-actions pathway so that emissions in one year match a selected target. Ranking uses lowest-MAC first. Generative AI does not select actions and does not invent emissions.

What the solver does

Select a target that already exists in Target Inputs. The target can be a custom near-term or long-term milestone, or an SBTi near-term pathway.

Choose current actions only, or current actions plus library templates. Templates are added from cheapest illustrative MAC to dearest.

One global scale factor is applied to selected multiplier-based actions. A multiplier cannot go below −1. An activity cannot go negative.

If the scaled plan still misses the target, the job reports the residual gap. The solver does not invent extra efficiency.

Target gap filled by cheapest actions first, with a residual gap if scale is limited Target year emissions Cheapest action, then next, then next Residual gap stays visible if the scale limit is reached. The calculation engine is deterministic.

What the solver does not do

  • It does not write new action types.
  • It does not change the science of BAU, external trends, and internal actions.
  • It does not guarantee a global cost minimum. Ranking is a greedy heuristic.
  • It does not replace a human review of the recommended plan.

Example: fill a 40 t gap

Three template actions fill a 40 t gap, cheapest first. Reduce the scale cap. If the cap is too low, a residual gap remains.

Example, not a calculation from your data

Attributed fill of the 40 t target

Filled
—
Residual gap
—
Target reached
—

    Related: MAC allocation and EAC valuation.